# Machine learning for surface prediction in ACTS

- Institution: CERN
- Department: Conferences
- Speaker: Benjamin Huth
- Year: 2021
- Language: English
- Subjects: Physics, Computer science, Earth and environment
- Source: [CERN](https://videos.cern.ch/record/3008039)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

We present an ongoing R&D activity for machine-learning-assisted navigation through detectors to be used for track reconstruction. We investigate different approaches of training neural networks for surface prediction and compare their results. This work is carried out in the context of the ACTS tracking toolkit..

0:00:00 Slide 1

0:01:22 Slide 2

0:02:44 Slide 3

0:04:06 Slide 4

0:05:28 Slide 5

0:06:50 Slide 6

0:08:12 Slide 7

0:09:34 Slide 8

0:10:56 Slide 9

0:12:18 Slide 10

0:13:40 Slide 11

## Lectures

1. [Machine learning for surface prediction in ACTS](https://invisiblenetwork.ai/learn/cern/3008039/42fbcb72f939), 14 min (CERN's player)